There is a substantial unmet need for more effective and targeted treatments for posttraumatic stress disorder (PTSD). The lifetime prevalence of PTSD is high in the population at an estimated 6.7%. One barrier for developing better therapies is our lack of understanding of the neural mechanisms in PTSD, with no validated biomarkers for PTSD. In addition to the affective symptoms in PTSD, attention deficits are persistent and linked directly to quality of life, disrupting relationships and employment. While important, current and past neuroimaging studies have largely focused on altered attention to threatening stimuli. However, non-threatening stimuli are experienced daily in civilian life and a few studies have demonstrated that neural responses to non- threatening stimuli are also altered in PTSD. A separate line of research demonstrates that altered resting networks are also associated with PTSD. Based on the influence of resting connectivity on neuronal firing thresholds, we expect that resting networks also play a role in abnormal task-evoked responses (e.g. attention). However, current studies largely examine either task-evoked responses or resting networks, but not the two in conjunction. This gap is a significant problem, because understanding how the brain transitions from rest to task is expected to play an important role in attention allocation. The objective in this application is to utilize the superior spatio-temporal resolution of magnetoencephalography (MEG) to examine resting state networks and responses to neutral, novel auditory stimuli using the auditory oddball (AOD) task. The central hypothesis is that individuals with combat-related PTSD will show alterations in rest MEG that will impact the ability to properly respond to non-threatening stimuli in day-to-day life and these associations will be related to PTSD symptom severity and attention measures. The central hypothesis will be tested via three Specific Aims: 1) Identify task- induced changes in amplitude and latency of the auditory network generators in participants with PTSD relative to non-PTSD combat controls (CC) via the AOD paradigm; 2) Identify resting MEG patterns associated with PTSD versus CC. Differences in attention performance between PTSD and CC are expected to be related to resting neural oscillations and 3) Examine the relationship between resting networks, task-based neural activation, symptom severity, and attention performance on neurocognitive tests. The approach is innovative because it will harness the excellent spatio-temporal resolution of MEG to determine underlying brain networks associated with Novelty and Target P3-related processing and then will combine this with an assessment of resting state networks to link resting state network functioning and task-related functioning to each other and to attention measures and symptom severity. The proposed research is significant because current treatments for PTSD, while effective, have known limitations and biomarkers for PTSD are lacking. Understanding the pathophysiology underlying prominent and disruptive attention symptoms in PTSD will ultimately guide the development of more directed and effective assessment and treatment.